Top Senior Data Engineer Jobs in Atlanta, GA

Develop and implement data solutions, pipelines, architectures, analytics, reports, and dashboards for clients. Apply Python, Java, ETL, business intelligence, and advanced analytics techniques to interpret complex data, improve operations, and support strategic decisions. Collaborate with stakeholders, manage client relationships, identify data challenges, and deliver high-quality managed services work while contributing to continuous process improvement.

Design, implement, and manage advanced data ecosystems and scalable ETL/ELT pipelines. Analyze complex problems, deliver data warehousing and governance solutions, mentor junior staff, and build client relationships while maintaining high standards and business-context awareness.

Lead design and implementation of enterprise data architecture and cloud-based data solutions. Manage large data engineering projects, develop data models and pipelines, ensure governance and security compliance, advise clients strategically, and build high-performing inclusive teams.

Architects and implements scalable data pipelines and enterprise data solutions spanning data lakes, warehouses, marts, and distributed systems. Designs dimensional and semantic data models, curated datasets, and Power BI reporting solutions with DAX, security, governance, and performance optimization. Establishes data lineage, metadata, stewardship, compliance, and secure access practices. Collaborates with stakeholders to translate business and reporting requirements into reusable analytics assets, while supporting AI and MLOps data pipelines across cloud and hybrid platforms.

Lead architecture and delivery of cloud data platforms, design scalable data warehouse and lake solutions, implement ETL/ELT frameworks, optimize platform performance and resilience, champion automation, governance, and mentor engineering teams to deliver enterprise analytics and data products.

Lead enterprise-scale data engineering initiatives, including the design, development, deployment, and maintenance of production data pipelines and scalable data platforms. Guide multidisciplinary teams, modernize analytics workflows using Python and SQL, develop shared libraries, and support Palantir Foundry adoption through training, integration, and architecture. Collaborate with stakeholders, provide technical presentations, and apply expertise in data architecture, Databricks, cloud platforms, and distributed data processing.

Design, build, and optimize scalable ELT pipelines into BigQuery, create dbt models and data models, implement data quality, observability, CI/CD, and IaC practices, and partner with stakeholders to deliver trusted enterprise data products.

Design, build, and optimize modern Azure and Databricks data platforms for clients. Develop batch and streaming ingestion pipelines, lakehouse and medallion architectures, dimensional models, and transformation workflows. Lead discovery sessions, requirements workshops, architecture discussions, and solution reviews. Recommend practices for governance, lineage, monitoring, DevOps, security, and data modeling while translating business needs into scalable technical solutions and communicating with technical and executive stakeholders.

Build, optimize, and maintain data pipelines, ETL processes, data architectures, AI solutions, and analytics platforms. Develop cloud-based solutions using Azure Functions and containerization, implement CI/CD workflows, integrate databases and APIs, and ensure data quality, monitoring, reliability, and documentation. Troubleshoot production issues, collaborate with cross-functional teams, and apply modern data engineering, AI, cloud, and DevOps practices.

Design, build, optimize, and maintain scalable batch and near-real-time data pipelines across on-premises and cloud platforms. Develop Snowflake data models, manage enterprise data integration and governance, implement data quality controls, and support reporting and analytics. Collaborate with data scientists, analysts, infrastructure, DevOps, privacy, and compliance teams. Troubleshoot pipeline issues, monitor performance, participate in architecture and Agile development activities, and mentor associate data engineers.

Lead design, build, and maintain scalable data pipelines, ETL processes, data models, and storage solutions. Support production data ecosystem, optimize performance, ensure data quality and security, integrate data sources/APIs, and provide technical guidance to teams while collaborating with stakeholders.

Design, build, and maintain scalable AWS-based ETL and data pipelines using Python, PySpark, and SQL. Implement Glue, Lambda, Step Functions, and event-driven integrations (SNS/SQS). Optimize data lake/warehouse solutions (S3, Athena, Redshift), implement monitoring, validation, and error handling, support API/JSON integrations, troubleshoot operations, automate deployments, and mentor junior engineers.

Build and maintain centralized pricing data infrastructure, scalable workflows, and data pipelines; integrate AI capabilities; deliver pricing tools, reporting, and governance to support data-driven pricing and budgeting across the firm.

Design, build, and maintain enterprise analytics solutions, semantic models, and reporting datasets using Microsoft Fabric, Databricks, SQL, Python, and BI tools. Lead data modeling, data quality, CI/CD, and performance optimization; translate business requirements into scalable analytics; mentor engineers and collaborate with architects and stakeholders to deliver trusted, self-service and executive reporting across the Americas.

Designs, builds, and maintains scalable data infrastructure, streaming and batch pipelines, and data products. Works with stakeholders to model, transform, and deploy data solutions using cloud, streaming, and ETL frameworks while ensuring governance, observability, and automated CI/CD deployments.

Design, develop, and maintain enterprise data solutions and pipelines using Azure data platform and Microsoft Fabric. Support data modeling, master data management, medallion architecture, data quality, and integrations to produce trusted, scalable data for analytics and BI.

Build, operate, and monitor ETL/ELT pipelines between marketing, sales, and operational systems into Databricks. Implement dimensional models, identity resolution, data quality checks, API integrations, and scheduled/event-driven syncs to support segmentation, attribution, and campaign activation. Maintain documentation, alerting, and runbooks.

Design, build, and operationalize complex data pipelines and products to support analytics and AI/ML. Analyze and transform source data, enforce data governance/security/quality, resolve high-complexity incidents, mentor team members, and partner with business stakeholders to deliver reusable, scalable data platform capabilities.

Leads data engineering for Payment Operations monitoring transformation. Designs and maintains Snowflake pipelines, tables, stored procedures, monitoring scenarios, KPI infrastructure, and data quality controls. Serves as the Snowflake subject matter expert, documents architecture and operational processes, guides technical partners, and translates business needs into scalable data solutions. The role requires production data engineering experience, advanced SQL, Snowflake expertise, job scheduling, pipeline operations, and stakeholder communication.

Lead design and delivery of the enterprise Data Platform including data lake, analytics, and certified data products. Architect solutions, automate pipelines, implement monitoring, mentor engineers, translate business needs into technical architectures, and document systems for sustainability.

Designs, builds, and maintains scalable ETL/ELT pipelines, data workflows, integrations, and curated Silver and Gold data assets. Supports analytics, reporting, machine learning, and operational applications through batch and streaming processing. Responsibilities include data ingestion, transformation, validation, quality management, automation, documentation, and performance optimization across enterprise data platforms. Partners with cross-functional teams, modernizes data processes, and mentors junior engineers.

Design, build, and maintain ETL/ELT pipelines and API integrations to ingest, cleanse, transform, and analyze infrastructure and cloud data. Produce analytics, dashboards, and executive reports; automate workflows and support near-real-time processing. Follow SDLC/DevOps practices (Git, CI/CD), ensure data governance, quality, lineage, and support incident, release, and compliance activities.

Design and build cloud-native, scalable data solutions for systematic trading. Partner with traders, quants, and architects to develop Snowflake-based ETL, data models, and pipelines; lead AI-driven capability adoption; ensure security and SDLC best practices.

The Senior Data Engineer at BeyondTrust designs and manages data infrastructure, creates ETL pipelines, and optimizes database performance while ensuring data governance.

Design, build, and maintain scalable ETL/ELT, batch and streaming data pipelines and platforms. Create reusable data models (dbt/Spark), ensure data quality and observability, collaborate with data scientists, analysts, and product teams, and mentor junior engineers while advancing data platform architecture and tooling.